Æ +41 78 838 33 84 • Q chen.liu@epfl.ch • Birth: 21st,Jan,1993

Education École polytechnique fédérale de Lausanne(EPFL) Lausanne, Switzerland + PhD in Computer Science 2017- Topic: adversarial robustness in deep learning. Supervisors: Prof. Sabine Süsstrunk, Dr. Mathieu Salzmann École polytechnique fédérale de Lausanne(EPFL) Lausanne, Switzerland + M.S in Computer Science 2015-2017 GPA: 5.73/6.00 Transcript Tsinghua University Beijing, China + B.ENG in Computer Science and Technology 2011-2015 GPA: 91.34/100.00 Rank 9/123 Transcript Graduated with Distinction

Research & Work Experiences Swisscom Digital Lab Feb, 2017–Aug,2017 + Lausanne Switzerland Internship - Automatic document summarization by sequence-to-sequence model with attention mechanism. Siemens Research (USA) Jul,2016–Feb,2017 + Princeton, New Jersey, USA Research Intern - Deep metric learning by triplet neural networks to automatically tune parameters of a 3D medical imaging renderer to obtain images of consistent visual effect.

Publications

+ Chen Liu, Zhichao , Mathieu Salzmann, Tong , Sabine Süsstrunk. "Hard Adversarial Instances Lead to Overfitting in Adversarial Training". Under submission. + Zhichao Huang, Chen Liu, Mathieu Salzmann, Sabine Süsstrunk, Tong Zhang. "Improving Adversarial Defense with Self-supervised Test-time Fine-tuning". Under submission. + Chen Liu, Mathieu Salzmann, Sabine Süsstrunk. "Training Provably Robust Models by Polyhedral Envelope Regularization". IEEE Transactions on Neural Networks and Learning Systems 2021. + Chen Liu, Mathieu Salzmann, , Ryota Tomioka, Sabine Süsstrunk. "On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them". Neural Information Processing Systems (NeurIPS) 2020. + Chen Liu, Ryota Tomioka, Volkan Cevher. "On Certifying Non-uniform Bounds against Adversarial Attacks". In International Conference on Machine Learning (ICML) 2019. + Ya-Ping Hsieh, Chen Liu, Volkan Cevher. "Finding the Mixed Nash Equilibria of Generative Adversarial Networks". In International Conference on Machine Learning (ICML) 2019. Oral Presentation in Smooth Games Optimization and Machine Learning Workshop in NeurIPS 2018. + Chen Liu, Shun Miao, Kaloian Petkov, Sandra Sudarsky, Daphne , Tommaso Mansi. "Consistent 3D Rendering in Medical Imaging". European Patent No. 18160956.1 - 1208.

Professional Service Reviewer: ICML, NeurIPS, ICLR

1/2 Awards & Honors

+ Qualcomm Innovation Fellowship Europe 2020 Finallist (15 in Europe) + ICML Travel Award (2019) + Microsoft Research Scholarship.(MSR sponsored student 2017 - 2019) + Outstanding Undergraduate Students in Department of Computer Science and Technology in Tsinghua University.(2015) + Scholarship of Academic Excellence in Tsinghua University.(2014) + Scholarship of Social Work in Tsinghua University.(2013) + Scholarship of Academic Excellence in Tsinghua University.(2013) + First Prize in Beijing College Student Physics Competition. (2012)

Mentorship EPFL Mater student: Ningwei . "Adversarial Robustness for Neural Ordinary Differential Equations." Yulun Jiang. "Adversarial Robustness for Multiple Threat Models". Ziqi . "Network Pruning in Adversarial Training". EPFL Bachelor student: Majdouline Ait Yahia. "Robust Binary Network".

Skills

+ Programming Language: Python, C/C++, Matlab, Java. + Deep Learning Tools: Pytorch, Tensorflow, Keras, Theano. + Natural Language: Mandarin(Native), English(Fluent).

External Links

+ Github: Codes. https://github.com/liuchen11 + Homepage: Projects. https://liuchen11.github.io

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